Adding Cues to Binary Feature Descriptors for Visual Place Recognition

Abstract

In this paper we propose an approach to embed multi-dimensional continuous cues in binary feature descriptors used for visual place recognition. The embedding is achieved by extending each feature descriptor with a binary string that encodes a cue and supports the Hamming distance metric. Augmenting the descriptors in such a way has the advantage of being transparent to the procedure used to compare them. We present a concrete application of our methodology, demonstrating the considered type of continuous cue. Additionally, we conducted a broad quantitative and comparative evaluation on that application, covering five benchmark datasets and several state-of-the-art image retrieval approaches in combination with various binary descriptor types.